Sooo, when you're hitting that Excel wall, it's usually cuz you need better memory management and parallel processing. Basically, Excel tries to load everything into RAM at once, which is why it dies on millions of rows. For your situation, I've been super satisfied switching to Python-based engines for the heavy lifting.

I recommend trying Pandas Library for Python vs Databricks Lakehouse Platform. If you're staying local, Pandas is the industry standard—it's incredibly flexible but can still chug if your RAM is low. But if you want real speed, Databricks is a beast for big data. It uses Spark to distribute the workload, so identifying anomalies across massive SQL datasets happens in seconds rather than minutes. It's highkey better for those tight deadlines. Honestly, just moving your cleaning scripts into a notebook environment makes a world of difference. Good luck!!

oh man, I feel u on the Excel struggle. Honestly, I've been there too many times where the file just hangs and basically dies lol. If you're looking for something that scales without breaking the bank, I highkey recommend checking out Mito for Python. It's basically a spreadsheet interface that sits inside a Jupyter notebook and generates Python code as you edit. It's free for individuals and seriously speeds up cleaning millions of rows.

Another solid budget-friendly move is using the Polars Library for Python. It's way faster than Pandas for big CSVs and totally free. If you want something more visual, Tableau Desktop Personal Edition is a classic, but honestly, for the best value, Dibi Desktop is great for SQL pattern finding and has a decent free tier. Using these over the years has saved me sooo much time compared to manual Excel hell. Good luck!!

imo Alteryx is better for speed than Knime, but both beat Excel. What's your budget like? Are you looking for a cloud-native setup or something local for security reasons??

Saving this thread

Seconding the recommendation above about switching to Python-based tools! Honestly, it's a total game-changer for speed when Excel starts dying on you. If you wanna go the DIY route, just use any of those big data processing engines from the Apache foundation. They're amazing for handling massive CSVs and scale like crazy. I've literally processed millions of rows in seconds... totally worth the learning curve if you need something local and fast!! gl

Honestly, if ur moving into millions of rows, you gotta think about data integrity first. Before picking a tool, i mean, how are you handling the validation? In my experience, jumping straight into AI automation can be RISKY because it might hallucinate patterns in dirty data. For your situation, I'd look into Apache Spark (PySpark). It's basically the industry standard for safe, distributed processing that wont crash ur system when things get heavy. Plus, it scales way better than Excel ever could. gl!

Works great for me

TIL! Thanks for sharing

Ok adding this to my list of things to try. Thanks for the tip!

Re: "TIL! Thanks for sharing" - it is amazing to see so many people jumping in on this because honestly its ridiculous how hard it is to just get tools to talk to each other these days! Like, I love the energy in this thread, but I have to vent for a second about how much of a nightmare compatibility has become. You try to move data from one industry standard to another and everything just falls apart. It drives me crazy!!

• The sheer number of broken ODBC drivers that havent been updated in a decade.
• Cloud platforms that refuse to play nice with local environments without a million config steps.
• Those annoying proprietary metadata headers that crash every tool you try to use. It is such a scam that these massive companies charge a fortune and still cant make their files compatible with basic open formats. It makes me so mad when I just wanna get my work done! Seriously love that we are all struggling through this together tho lol!